Open AccessComparative study of microarray and experimental data on Schwann cells in peripheral nerve degeneration and regeneration: big data analysis
Author(s) -
Ulfuara Shefa,
Junyang Jung
Publication year - 2019
Publication title -
neural regeneration research/neural regeneration research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.93
H-Index - 38
eISSN - 1876-7958
pISSN - 1673-5374
DOI - 10.4103/1673-5374.250632
Subject(s) - microarray analysis techniques , microarray , schwann cell , gene chip analysis , microarray databases , biology , gene , dna microarray , regeneration (biology) , gene expression , computational biology , gene expression profiling , bioinformatics , genetics , microbiology and biotechnology
A Schwann cell has regenerative capabilities and is an important cell in the peripheral nervous system. This microarray study is part of a bioinformatics study that focuses mainly on Schwann cells. Microarray data provide information on differences between microarray-based and experiment-based gene expression analyses. According to microarray data, several genes exhibit increased expression (fold change) but they are weakly expressed in experimental studies (based on morphology, protein and mRNA levels). In contrast, some genes are weakly expressed in microarray data and highly expressed in experimental studies; such genes may represent future target genes in Schwann cell studies. These studies allow us to learn about additional genes that could be used to achieve targeted results from experimental studies. In the current big data study by retrieving more than 5000 scientific articles from PubMed or NCBI, Google Scholar, and Google, 1016 (up- and downregulated) genes were determined to be related to Schwann cells. However, no experiment was performed in the laboratory; rather, the present study is part of a big data analysis. Our study will contribute to our understanding of Schwann cell biology by aiding in the identification of genes. Based on a comparative analysis of all microarray data, we conclude that the microarray could be a good tool for predicting the expression and intensity of different genes of interest in actual experiments.